Essays on Economics of Regulation
Open Access DepositedChapter 1 is based on research joint with Tara M. Sinclair. Businesses regularly cite the regulatory environment as a factor influencing their production and hiring decisions, but there is little research quantifying the sentiment and uncertainty around regulation. This chapter presents measures of sentiment and uncertainty about the U.S. regulatory environment using natural language processing of an original news corpus from leading U.S. newspapers. I build monthly indexes of regulatory sentiment and regulatory uncertainty and categorical indexes for 14 regulatory policy areas from 1985 through 2021. Impulse response functions indicate that a negative shock to regulatory sentiment is associated with large, persistent drops in future output and employment, while increased regulatory uncertainty overall has a nonsignificant or transitory impact. Economic outcomes are particularly sensitive to sentiment and uncertainty around certain regulatory areas, including transportation, consumer safety and health, general business and trade, and energy regulations. Chapter 2 is based on research joint with Xiaohan Ma. This chapter examines the economic impact of uncertainty surrounding U.S. regulatory policies of the energy sector. I first construct a monthly-frequency measure of regulatory uncertainty related to oil and gas production using natural language processing on over 600,000 U.S. newspaper articles published from 1985 to 2021. I then conduct empirical analysis via structural VAR models with the constructed oil regulatory uncertainty index, oil market variables, and aggregate economic data. The impulse response functions suggest that an increase in oil regulatory uncertainty reduces oil production and drilling activity and negatively affects national and state-level economic outcomes. Chapter 3 examines the interplay between regulation and innovation. Some innovations are developed to comply with or circumvent legal and regulatory requirements. While these regulation-driven innovations can generate societal benefits, they may also incur unintended economic costs. This chapter explores this unique type of innovation and examines its relationship with firm dynamics, creative destruction, and economic growth. I present a simple Schumpeterian model demonstrating how regulation-driven innovations can serve as a strategy for firms to achieve higher growth, deter competitors, and reduce the rate of creative destruction. Guided by the model's implications, I identify regulation-driven innovations from U.S. patents issued between 1976 and 2020 by measuring the degree of alignment between patents and federal regulations. I construct this measure by estimating textual similarities between patent documents and regulatory texts using natural language processing techniques. Linking the measure with patent- and firm-level data, I find that innovation-regulation alignment is positively associated with the economic value of patents and the growth in size and market power of innovating firms. At the aggregate level, however, the static gains for innovating firms fail to offset the dynamic social costs from reduced reallocation and competition.
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